Images from visualcomplexity.com a gallery of over 700 network visualization projects – visual complexity is cool because topics of interest can be filtered – the images here represent “art visualizations”

Speed of Communication, and insight are what what data visualization is all about. THE VISUALS ARE THE VEHICLE.the &quot;main goal of data visualization is to communicate information clearly and effectively through graphical means. – FriedmanVisualization is a way of thinking and communicating.

Who is familiar with this visualization? This this a visualization called Mapping Time by Lev Manovich, 2009.Lev Manovich is professor of visual arts at UC–San Diego,and is director of the Software Studies Initative. Manovich and software studies analyzes very large visual data sets to discover previously unseen patterns in cultural data. He tends to work with current cultural media. Thisa montage of every Time magazine coverpublished between1923 - 2009. 4,535 images placed side by side left to right.Data visualization reveals hidden patterns about the world, so what can we learn here? Medium. Hue. Color vs Black and White. Brightness. Contrast &amp; Saturation (increase and reversal) Content. This visualization also reveals a “metapattern”:almost all changes are gradual,emerging slowly over a number of months, years or even decades.Here question are raised about the broader context in which the changes took place, the nature of visual style, and the idea of historical patterns.

TimelineJeremy Douglass and Lev Manovich .Once you have your data and image sets established, you can manipulate them to see if other patterns emerge. These visualizations are plotted to reveal differences in saturation over time. It is perhaps not surprising to see that the intensity (or “aggressiveness”) of mass media as exemplified by Time covers gradually raises up to the end of the 1960s as manifested by changes in saturation and contrast. Manovich’s theory about the height of saturation at the end of the sixes – verses mine and verses jims.

Mondrian vs Rothko: footprints and evolution in style space On the left 128 paintings by Mondrian; the right, 151 paintings by Rothko. The paintings are organized according to their brightness mean (X-axis) and saturation mean (Y-axis). Displaying them side by side reveals their comparative &quot;footprints&quot; - the parts of the space of visual possibilities they explored. We can see the relative distributions of their works - the more dense and the more sparse areas, the presence or absence of clusters, the outliers, etc.The visualizations also show how Mark Rothko - the abstract artist of the generation which followed Mondrian - was exploring the parts of brightness/hue space which Mondrian did not reach (highly saturated and bright paintings in the upper right corner, and desaturated dark paintings in the left part).

iBenShneidermananother important figure within the InfoViz world (professor in the department of Computer Science, founding director of the Human Computer Interaction Laboratory of the U of Maryland. )Treemaps graphically represent information about objects by dividing the display into areas (typically rectangles) that are proportional to the size of each object. By recursively nesting the areas, treemaps enable quantitative comparisons of attribute values while showing their hierarchical relationships. Each rectangles on this map represents a post aboutFlowingData. Size represents number of views and the brighter green indicates more comments.

Here we see &quot;old cultural countries vs &quot;young cultural countries (as measured by biennale launches in each country. This is a visualization build in Many Eyes.Many Eyes automatically ads thenumbers of all biennales started in a particular country. Since the biennales which started before 1990 have negative numbers, and biennales which started after 1990 have positive numbers, the sum of these numbers indicates of the country&apos;s cultural investments are in the past or are recent. For example, the number for US (based on 4 biennales) is -129, while the number for China is 43.

Does anyone know or could guess what this represents? Imaginary Forces – Animated slivers of 20,000 images from MOMA’s digital collections. Iit is meant to act as a “theatrical transitional curtain”. What does this teach us? Not much, but pedagogy is not the intent of the project – it is meant to be alternative way to interact and experience the museums collections.

Manoviich goes on to say in this paper that the first conference on visualization in humanities took place at The MIT in May 2010).” –Manovich was there as speaker, Schniderman was a speaker, Drucker gave the keynote, and I was there as well…

Humanities + Digital: Visual Interpretations Conference. Aesthetics, Methods, and Critiques of Information Visualization in the Humanities, Arts, and Social SciencesMay,2010 at MITOrganized by HyperStudio – Digital Humanities at MITThis conference was on soft money so it is unfortunately not an annual event, but it is possible that there will be another one, so keep an eye out for that. Joanna Drucker gave the keynote, Manovich was there, Schneiderman was there, and I was there as well.

Minard&apos;s thematic map of Napoleon&apos;s march is perhaps the single best-known statistical graphic of the nineteenth century, So, what makes a successful visualization? Let’s look at the amount of information that is conveyed in this graphic. There are six separate variables that were captured within it. And it tells a story.First, the line width continuously marked the size of the army. Second and third, the line itself showed the latitude and longitude of the army as it moved. Fourth, the lines themselves showed the direction that the army was traveling, both in advance and retreat. Fifth, the location of the army with respect to certain dates was marked.

So, What will “the impact of information visualization on museum practice and research in the coming years?”

(Cultural Analytics) Antoher speaker at the MIT conference was Maximilian Schich, and some of may have attended his sessions at THATCampNE, he an art historian and focuses on complex networks in art history and archaeology. He combines art historical expertise with the science of complex networks and will contribute to the emerging field of web science. He works with image matrices as a visualization method for large image classification networksto uncover hidden patterns of co-relation, beyond the reach of regular searching and browsing of either images or classification criteria.And I have no idea how he does it, even though I have heard him speak twice. I mention Schich because it seems that Elli Mylonas and I have gotten confirmation from Max that he will come to Brown to give a talk sometime in December, so you will have the chance to be baffled also. He also will be on a panel at CAA &quot;Information Visualization as a Research Method in Art History” CAA 2012 (Los Angeles)

http://dev.stg.brown.edu/projects/mjplab/Others_visualizations/index.htmlThe main purpose of this site is to do cool things with the data that the Modernist Journals Project has generated over the course of digitizing magazines from the early 20th century. All of the Protovis graphics of Others that appear on the page below were created by Jean Bauer and Elli Mylonas at the Library&apos;s Center for Digital Scholarship at Brown University.

Transcript

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Using Vision to Think about the HumanitiesDATA VISUALIZATIONS

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“The next big idea in language, history and the arts?” DATA -New York Times, November 16, 2010. Who has rich data and image sets? CULTURAL INSTITUTIONS!

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Visualization “makes the job of our visual system easier, but it’s not going toexplain a pattern. It confronts you with something you wouldn’t notice otherwise,confronts you with new cultural facts. You see things that, probably, nobody hasnoticed before, new cultural patterns that you now have to explain.” Lev Manovich . Graphing Culture. Humanities. Spring 2011

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“by extracting and graphing this data it will help us understandpatterns and explore trends in a painter’s life and work.” - Lev Manovich

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Ben Shneiderman focuses on designing technologies that allow the "visualization of things not visible.” In the early 90’s Scheiderman developed The treemap,an area-based visualization where the size of each rectangle represents a metric .

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Visualizations also can help Cultural Institutions/Organizationsgather information about themselves. Here we look at biennalelaunches in various countries, and can determine the “oldcultural countries” from the “young cultural countries.

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In a 2009 essay Manovich evoked the term “cultural analytics” “a new paradigm for the study, teaching, and public presentation of cultural artifacts, dynamics, and flows.” the general idea of cultural analytics is to apply data visualization and analysis techniques traditionally associated with the so-called hard sciences—graphing, mapping, diagramming, and so on—to the study of visual culture.“Direct visualizations methods will be particularly important for humanities, mediastudies and cultural institutions which now are beginning to discover the use ofvisualization, but which eventually may adopt it as a basic tool for research,teaching and exhibition of cultural artifacts.” “Humanists always focused on analyzing and interpreting details of the culturalobjects. This is one of the key differences between humanities and sciences – atleast, as they were practiced until now. The former are interested in particularartifacts (which can be taken to exemplify larger trends); the latter are interested ingeneral laws and models.” - Lev Manovich. Date. What is Visualization?

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The conference explored new ways to design data and metadata structures sothat their visual embodiments function as “humanities tools in digitalenvironments.”“The goal was to get beyond the notion that information exists independently ofvisual presentation, and to rethink visualization as an integrated analyticalmethod in humanities scholarship.” -Johanna Drucker

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“Information visualization has the potential to transform both museum practice and research in to museum collections.”“In the museum field, talented individuals have begun to experiment withvisualization tools to represent collections, visitors, and a range of othermuseum activities, using a variety of visualization styles and methods andasking a range of questions about collecting practice, allocation of museumresources, and visitor responses to onsite and online programs. techniques borrowed from the digital humanities community have begun to appear in primary research about collection objects. Because of its highly complex (and often visual nature), museum data can represent both new challenges and possibilities for infoviz specialists and for the museum professionals and scholars who are their audiences.” - Information Visualization and Museum Practice: MCN 2010

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The Modernist Journals Project:a joint project of Brown University and The University of Tulsa MJP Lab: Visualizing an Entire Journal: Others